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Effectiveness of rehabilitation training on radiotherapy-related abnormalities of voice function in head and neck cancer patients: A systematic review and meta-analysis
Background Abnormal speech function caused by radiotherapy will affect the normal communication of patients with head and neck cancer (HNC) and even interrupt their social life. Rehabilitation Training is widely used to improve articulatory abnormalities in patients with HNC. However, the effectiveness of these rehabilitation measures in restoring the voice function of HNC patients is still unknown. Objective This study aimed to systematically examine the effects of rehabilitation training on radiotherapy-related voice function and quality of life in patients with HNC. Methods The databases PubMed, Web of Science, EMBASE, Cochrane Library, CINAHL, CNKI, Wan Fang, and SinoMed were searched for studies published from inception through October 2024. Randomized controlled trials of rehabilitation training to improve voice function abnormalities associated with radiotherapy for HNC were included, and two investigators independently performed the literature review. Meta-analysis was performed using RevMan 5.4 software to determine statistical heterogeneity based on P-values and I2 values. Results 13 randomized controlled trials involving 710 participants were included. Meta-analysis showed that rehabilitation training significantly affected the patients’ maximum phonation time(MD=1.53, 95%CI=[0.83, 2.23], P<0.0001, Grade Moderate), smoothed cepstral peak prominence(MD=-0.59, 95%CI=[-0.89, -0.29], P=0.0001, Grade Moderate), social communication abilities(MD=-2.60, 95%CI=[-5.14, -0.07], P=0.04, Grade Moderate), and quality of life(MD=8.49, 95%CI=[3.06, 13.92], P=0.002, Grade Moderate). Conclusions Rehabilitation training is an effective approach for ameliorating abnormal voice functions after radiotherapy for HNC. However, there is no consensus on the optimal frequency, periodicity, and follow-up of interventions for rehabilitation training. More studies are still required to determine the optimal intervention effect for ameliorating speech function abnormalities in patients with HNC after radiotherapy.
The mediating role of cognitive arousal in the relationship between impulsivity and sleep quality among college students: a random intercept cross-lagged panel analysis
DNA-based floristic survey of red algae (Rhodophyta) growing in the mesophotic coral ecosystems (MCEs) offshore of Tanegashima Island, northern Ryukyu Archipelago, Japan
A molecular-based floristic survey of marine red algal biodiversity was conducted offshore Tanegashima Island, which is located at the northern end of mesophotic coral ecosystems (MCEs), in the Ryukyu Archipelago, Japan. This study provides the first comprehensive catalog of red algae comprising the sublittoral marine flora of offshore Tanegashima Island, Japan, and represents the first exhaustive molecular-assisted survey of red algal marine flora in Japan. Morphological and molecular analyses using plastid-encoded rbcL and mitochondrion-encoded cox1 genes revealed a total of 129 species, which included nine newly recognized species in Japan. Morphologically, 82 species were assigned to known species. Among the 82 species, 17 included cryptic species, and 25 appeared to have misapplied names. The remaining 47 species could not be identified to the species level, which indicates the necessity of a detailed reference library containing validated DNA barcodes and further taxonomic studies based on morpho-molecular analyses.
N,N-dimethylacetamide blocks inflammation-induced preterm birth and remediates maternal systemic immune responses
Color correction methods for underwater image enhancement: A systematic literature review
Underwater vision is essential in numerous applications, such as marine resource surveying, autonomous navigation, objective detection, and target monitoring. However, raw underwater images often suffer from significant color deviations due to light attenuation, presenting challenges for practical use. This systematic literature review examines the latest advancements in color correction methods for underwater image enhancement. The core objectives of the review are to identify and critically analyze existing approaches, highlighting their strengths, limitations, and areas for future research. A comprehensive search across eight scholarly databases resulted in the identification of 67 relevant studies published between 2010 and 2024. These studies introduce 13 distinct methods for enhancing underwater images, which can be categorized into three groups: physical models, non-physical models, and deep learning-based methods. Physical model-based methods aim to reverse the effects of underwater image degradation by simulating the physical processes of light attenuation and scattering. In contrast, non-physical model-based methods focus on manipulating pixel values without modeling these underlying degradation processes. Deep learning-based methods, by leveraging data-driven approaches, aim to learn mappings between degraded and enhanced images through large datasets. However, challenges persist across all categories, including algorithmic limitations, data dependency, computational complexity, and performance variability across diverse underwater environments. This review consolidates the current knowledge, providing a taxonomy of methods while identifying critical research gaps. It emphasizes the need to improve adaptability across diverse underwater conditions and reduce computational complexity for real-time applications. The review findings serve as a guide for future research to overcome these challenges and advance the field of underwater image enhancement.
Author Correction: Luminal androgen receptor subtype and tumor-infiltrating lymphocytes groups based on triple-negative breast cancer molecular subclassification
Water production efficiency and economic benefits under diversified planting modes of intercropping-multiple cropping in arid regions
Diversified planting patterns are important measures to improve the comprehensive grain production capacity, alleviate the contradiction between grain crops and forage planting, and enhance water production efficiency. In order to explore the suitable diversified planting modes in the Yellow River irrigation area of Ningxia, a total of 4 treatments were designed, including wheat-maize silage intercropping and multiple planting of sorghum-sudangrass hybrid after wheat harvest (T1); wheat-cabbage intercropping, multiple planting of oil sunflower after wheat harvest, followed by maize silage planting after cabbage harvest (T2); sole wheat, after the harvest of wheat, half of the land is used for multiple plantings of maize silage, and the other half is used for multiple plantings of oil sunflower (T3); and sole maize silage (T4). The results showed that all diversified planting modes can increase biomass and land equivalent ratio compared to the control monoculture. The T2 had the highest total biomass and land equivalent ratio, the two-year average was 79.68 t/ha and 2.27, respectively. The highest biological yield per cubic meter of water was achieved by T3, with an average of 12.65 kg/m3 over two years. T1 achieved the highest output value per cubic meter of water, with 16.81 Chinese Yuan/m³ over 2 years. In both T1 and T2, due to the increased spacing between intercropping crops, as well as sufficient water and fertilizer supply and developed root system, maize silage is at a competitive advantage, with a interspecific relative competitive ability between 0.059–0.234. When maize silage and oil sunflower are planted simultaneously, due to the fast growth rate of oil sunflower, it is the dominant crop, the interspecific relative competitive ability in 2022 and 2023 were 0.164 and 0.137, respectively. The net benefit of T1 was the highest, with an average total net income of 84,950 Chinese Yuan/ha over 2 years. It can be seen that diversified planting patterns can improve the yield and economic benefits per unit land area, and are a highly promising planting pattern.
Discrepancy on the quality characteristics of soluble dietary fiber in wild Rosa roxburghii Tratt fruits from different regions
Correction: Can the digital economy contribute to rural revitalization? A case of from China?
Investigating the PI3K/AKT/mTOR axis in Buzhong Yiqi Decoction’s anti-colorectal cancer activity
The prevalence of Tramadol abuse and associated factors among Hawassa University students, Hawassa, Ethiopia
Introduction Tramadol abuse is a current public health concern in Ethiopia. Drug abuse including that of tramadol is a significant public health issue that causes health, economic, and social problems to individual drug users, their families, the community, and the entire nation. Therefore this study delivers information regarding current tramadol abuse among students of an Ethiopian University. Objective The aim of this study is to assess the prevalence of tramadol abuse and associated factors among Hawassa university students, February to June 2023. Methods and materials A cross-sectional study was performed among 402 randomly selected Hawassa university students. Data was collected from participant through self-administered researcher made questionnaire using kobo toolbox software applications. Data from kobo toolbox were directly exported to and analyzed by using SPSS version 26 software. Binary logistic regression was applied to identify the factors associated with tramadol abuse. In the final model, Adjusted Odds Ratio, and 95% CI was used to measure the strength of association and P-value less than 0.05 considered statistically significant. Result A total of 402 students were enrolled in this study of which 46 students (11.4%) [95% CI 8.5–14.7] had history of tramadol abuse once in their lifetime with 23.9% of them were active tramadol abuser with some dependence behaviors. The result of multivariate analysis shows that having a friend who use drugs [AOR = 1.691, 95% CI (0.718–3.980), p = 0.041], knowing about tramadol [AOR = 13.766, 95%CI (3.003–63.113), p = 0.001] and having the history of taking tramadol with physicians prescription in their life time [AOR = 7.960, 95%CI (3.603–17.587), P < 0.001] were the significant predictors of tramadol abuse. Conclusion The life time prevalence of tramadol abuse among university students is high and it demands attention of government and the general public.
A caveat about the use of trigonometric functions in statistical tests of nutritional geometry models
Adoption of K-means clustering algorithm in smart city security analysis and mythical experience analysis of urban image
Objective An information security evaluation model based on the K-Means Clustering (KMC) + Decision Tree (DT) algorithm is constructed, aiming to assess its value in evaluating smart city (SC) security. Additionally, the impact of SCs on individuals’ mythical experiences is investigated. Methods An information security analysis model based on the combination of KMC and DT algorithms is established. A total of 38 SCs are selected as the research objects for practical analysis. The practical feasibility of the model is assessed using the receiver operating characteristic (ROC) curve, and its performance is compared with that of the Naive Bayes (NB), Logistic Regression (LR), Random Forest (RF), Support Vector Machine (SVM), and Gradient Boosting Machine (GBM) classification methods. Lastly, a questionnaire survey is conducted to obtain and analyze individuals’ mythical experiences in SCs. Results (1) The area under the ROC curve is significantly higher than 0.9 (0.921 vs. 0.9). (2) Compared to the NB and LR algorithms, the security analysis model based on the combination of KMC and DT algorithms demonstrated higher true positive rate (TPR), accuracy, recall, F-Score, AUC-ROC, and AUC-PR. Additionally, the performance metrics of RF, SVM, and GBM are similar to those of the KMC+DT model. (3) When the attributes are the same, the difference in smart risk levels is small, while when the attributes are different, the difference in risk levels is significant. (4) The support rates for various types of new folk activities are as follows: offline shopping festivals (17.6%), New Year’s Eve celebrations (16.7%), Tibet tourism (15.6%), spiritual practices (16.2%), green leisure (16.0%), and suburban/rural tourism (15.8%). (5) High-risk cities (Grade A) showed stronger support for modern activities such as offline shopping festivals and green leisure, while low-risk cities (Grades C and D) tended to favor traditional cultural activities. Conclusion The algorithm model constructed in this work is capable of effectively evaluating the information security risks of SCs and has practical value. A good city image and mythological experience are driving the development of cities.
Characteristics stochastic analysis of long and narrow deep excavations under soil spatial variability
Abstract The mechanical properties of soil, resulting from the weathering of rocks through physical and chemical processes, exhibit spatial variability. This variability introduces uncertainties in the design and characteristics of excavation projects. To address these uncertainties caused by soil spatial variability, safety factors are commonly used in excavation design. However, using the same safety factor for different indicators of soil spatial variability is illogical. Therefore, specialized research on the characteristics of deep excavations in the context of soil spatial variability is necessary, as it provides the theoretical basis for rational excavation design. In this study, we assumed that soil parameters follow a lognormal distribution, while spatial correlation adheres to a Gaussian function. We developed a random finite element algorithm for deep excavations, which incorporated Python programming and the ABAQUS computational platform. This algorithm was created within the framework of random field theory and Monte Carlo simulation. The results of our study indicate that, influenced by soil spatial variability, the lateral wall movements and ground surface settlements exhibit discrete distributions near the deterministic results. The maximum deformation of the excavation follows a normal distribution, while the pattern of ground surface settlements demonstrates diversity and chaotic characteristics. The extent to which soil spatial variability affects deep excavations is correlated with indicators of this variability. As the coefficient of soil spatial variability increases, the diversity and chaotic characteristics of ground surface settlements become more prominent. The locations of maximum ground surface settlement and maximum deformation becomes more scattered. Consequently, the probability of excavation failure increases, and the reliability index of the excavation decreases. In summary, soil spatial variability significantly impacts deformation prediction and safety control during the design and construction stages of deep excavations. Therefore, it is crucial to consider the influence of soil spatial variability when designing deep excavations, based on the variability indicators.
Research on the evaluation of China’s Supply Chain Finance policy based on text mining
Supply Chain Finance (SCF) aims to manage the capital flow, logistics flow, and information flow of small and medium-sized enterprises (SMEs) in the upstream and downstream of the supply chain while optimizing supply chain risk control. Like other types of financial services, the development of SCF is highly influenced by policy factors; however, related research remains relatively limited. This study aims to explore the current state of SCF policymaking in China and provide scientific recommendations for the development of SCF from a policy perspective. First, using the BERTopic model, 3,439 SCF-related academic papers and 181 central-level SCF policy texts from the CNKI database were analyzed for thematic clustering. Then, by comprehensively considering the thematic distribution of SCF research and the operational characteristics of SCF, the Policy Modeling Consistency (PMC) Index model was constructed to evaluate SCF policy texts. The findings reveal several issues in China’s SCF policymaking: limited thematic focus, fluctuating levels of policy formulation, and significant homogenization of policy content. The study proposes several optimization recommendations for SCF policies, including expanding the scope of policy focus, fostering synergy among different types of policies, diversifying the use of policy tools, and broadening the range of target groups addressed by policies.
Relational information framework, causality, unification of quantum interpretations and return to realism through non-ergodicity
Abstract In the framework of relational information, we explore analogs of physical theories and their properties. Specifically, we investigate the causal characteristics of relational information, examining how initial knowledge impacts future relational understanding of the universe/system. To achieve this, we establish a parameter space defining relational structures called dendrograms, exhibiting causal properties akin to those of Minkowski metric. Subsequently, we propose a statistical-dynamical model on this Minkowski-like parameter space, unifying Bohmian and Many Worlds interpretations of quantum theory in the framework of relational information. Additionally, we provide an analytical proof of the non-ergodicity of the relational information framework, revealing CHSH inequality violations as an emergent phenomenon. Our focus on relational information underscores its significance across scientific disciplines, where a single measurement or observation lacks meaning without context.
Leveraging time for better impulse control: Longer intervals help ADHD children inhibit impulsive responses
Children diagnosed with an Attention Deficit Hyperactivity Disorder (ADHD) often exhibit impulsivity and timing difficulties. Here, we investigated whether children (mean age = 9.9 years) with combined type ADHD, comprising both hyperactive-impulsive and inattentive symptoms, could use the temporal predictability of an event to help inhibit impulsive behaviour. In an adapted Simon task, we measured the effects of temporal predictability on the speed and accuracy of choice reaction times (RT) to targets appearing after short or long intervals. Temporally predictive information was conveyed either explicitly (visual cues) or implicitly (cue-target interval). Analysis of RT distributions allowed us to decompose impulsive behaviour into two key elements: the initial urge to react impulsively, and the subsequent ability to inhibit any impulsive erroneous behaviour. Both healthy controls and ADHD children could use temporal predictability conveyed by temporal cues and the length of the trial to speed their RT. However, in healthy children both explicit and implicit temporal predictability impaired inhibition of impulsive responses. In turn, although children with ADHD had stronger tendency for impulsive responding and abnormal patterns of inhibition as compared to controls, the temporal predictability of the target did not exacerbate these effects. Indeed, responding to targets appearing after long, rather than short, intervals improved inhibition in ADHD children. Taken together, our results suggest that children with ADHD can make use of longer preparatory intervals to help inhibit impulsive behaviour.
Hydrocarbon generation potential and geochemical characteristics comparison of source rocks in the Southwestern Qaidam basin, China
Abstract A primary source rock has developed in the Upper part of the Lower Ganchaigou Formation (E3 2) in the southwestern Qaidam Basin, China. This basin features typical brackish-saline lacustrine deposits, necessitating careful selection of appropriate standards for evaluating hydrocarbon generation potential. The presence of multiple sets of source rocks and complex migration pathways has led to the accumulation of mixed-source oils, complicating the relationship between crude oil and source rocks and the establishment of hydrocarbon migration system. To address these challenge, 113 source rock samples were analyzed using Rock–Eval 6, gas chromatography-mass spectrometry and microphotometer. R-type clustering and principal component analysis were employed to select two out of five biomarker parameters that reflect water salinity and parent material sources for Q-type clustering. The results indicate that the E3 2 source rock exhibits fair hydrocarbon potential and is predominantly composed Type I and Type II1 kerogens. It remains in a low-maturity to mature stage, with deposition occurring in environments characterized by either strong reduction and high salinity or relatively weak reduction and low salinity. The oil is derived from nearby source rocks in the Hongshi, Yingxiongling, and Chekrike-Zahazquan depressions. This study provides new insights into source rock evaluation and oil-source relationship analysis.
Deformation and energy damage characteristics of granite-concrete composite under uniaxial compression
To investigate the influence of the fractured rock-concrete interface on the mechanical response of the rock mass and engineering, the mechanical properties and energy evolution of granite-concrete composite specimens with 16 different fracture inclinations were examined through uniaxial compression particle flow simulation. The results show that when the relative area is constant, the larger the fracture dip angle is, the compressive strength of the composite body presents a similar “peak” type change; the dip angle appears to have the maximum value at 60 o and 90o and the minimum value at 0 o and 30 o, while the peak elastic modulus presents a “waterfall” type change, and the maximum value appears at 90o. The crack types were classified as shear cracks, tensile cracks, secondary shear cracks, secondary tensile cracks, shear-dominated mixed cracks, and tension-dominated mixed cracks. From the crack distribution, it was found that the root cause of crack initiation and propagation was affected by the crack inclination angle. The damage degree increased gradually with the increase of crack inclination angle. When the crack inclination angle was constant, the deterioration degree of the specimen weakened with the increase of relative area s. The elastic energy consumption ratio increases with the shaft deformation, first rapidly and steeply decreasing to the steady inflection point, then slowly increasing to the rapid and steep increase, showing a “fishhook” shape. When the strength failure occurs, the growth speed increases suddenly, and the elastic energy consumption ratio increases suddenly after the K peak. This phenomenon can be used as the basis for the occurrence of strength failure and can be used as a qualitative judgment of strength failure.